RecoLift: An Android Wear Fitness Tracker for Strength Training
Aranguiz, Dario
Loading…
Permalink
https://hdl.handle.net/2142/78982
Description
Title
RecoLift: An Android Wear Fitness Tracker for Strength Training
Author(s)
Aranguiz, Dario
Contributor(s)
Choudhury, Romit R.
Issue Date
2015-05
Keyword(s)
Android
strength training
wearable
inertial sensors
Abstract
Despite the plethora of fitness trackers on the market, few monitor signals
other than number of steps and heart rate. With the increasing mainstream
acceptance of general-purpose smartwatches, however, we have the capability
to track more complex activities. We propose RecoLift, an Android-based
system to track exercises and repetitions in weight training and bodyweight
training activities based on the work of Morris et al. (2014). Our goal
is a system which provides feedback to the user in an autonomous, online
fashion, harnessing both smartwatch and smartphone sensors. This system
is separated into three key phases: segmentation, during which we use the
periodicity of the signals to determine if an exercise is being performed, recognition, which calculates signal features to determine which exercise is being
performed, and counting, which uses periodicity to calculate the number of
repetitions in a set. Our evaluations trained on a single user show perfect
exercise recognition, with 80% of repetitions on average being within 1 repetition
of the true count.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.